Clinical therapeutic protocol and prognosis of patients diagnosed with various disease conditions, such as cancer, may be drastically different depending on accurate diagnosis of underlying molecular mechanism as well as identification of all driver mutations and auto and paracrine effects. In addition, many diseases that may be phenotypically (pathologically) similar can have very different underlying causes. Cancers, for example, are extremely diverse; therefore, accurate diagnosis and stratified therapeutic approaches are critical for effective treatment. In patients diagnosed with cancer, many of the signaling pathways that control cell growth and differentiation are regulated in an abnormal fashion, particularly the balance between cell proliferation and cell death. Many of these pathways are activated due to the accumulation of mutations in key proteins, termed “driver mutations” or due to the secretion of growth factors and cytokines by tumor cells or stromal cells and reactivation of receptors on the tumor plasma membrane that activates these signaling pathways. These mutations encompass a wide range of processes but all share the ability to endow the cells with oncogenic activity. Hence, targeting such driver mutations with specific inhibitory drugs (“targeted therapy”) is a main goal in cancer therapy. For example, lung cancer may possess many underlying participating factors (e.g. EGFR mutations and the ALK-ELM4 translocation) each of which require a different therapeutic approach. Likewise, the treatment of breast cancer is dictated by the underlying molecular profile (such as ER/PR expression or HER2 amplification). The interplay between the different pathways is highly complex and is tumor-specific and in most cases patient specific. Full understanding of the patient specific tumor underlying signaling mechanism is required to determine the best combination of targeted therapy drugs are likely to be effective by interrupting the aberrant signaling pathways to inhibit cell division and induce cell death. The heterogeneity of tumors (genetic polymorphism) among individuals has a profound impact on drug efficacy as well as the likelihood of undesirable off-target side effects and ultimately the survival rate.
Among some 320 known signaling pathways in humans, about 50 signaling pathways are directly or indirectly involved in tumor growth and progression. There is an unmet need for a platform that enables the identification of the profile of the patient's tumor activated signaling pathways by monitoring the activation of various signaling proteins (such as, for example, membrane-localized and/or intracellular receptors and signaling proteins), in viable test cells.
The complexity and heterogeneity of cancer demands a more sensitive and discerning diagnostic approach that mirrors the tumor signaling pathway in a qualitative and quantitative manner and enables accurate selection of stratified therapy. The current state of the art is that few individual markers can be used to predict drug efficacy and toxicity. Moreover, the suitability of whole-genome sequencing (next generation sequencing) for selection of targeted therapy is limited due to the large pool of mutations accumulating within the tumor and the limited repertoire of identified driver mutations. In addition, whole-genome sequencing does not reveal auto and paracrine stimulation which are major drivers in tumor proliferation.
Thus, there is unmet need in the art for methods and systems that provide for a patient specific diagnostic platform, which is both cost and time effective, and which have the ability to specifically identify patient specific driver mutations and auto-paracrine mutations based on their aberrant activity and can consequently predict a specific, personalized and optimized treatment.